MongoDB Atlas for Government on AWS Achieves FedRAMP® Moderate Authorization

Salman Baset and Imani Tate
February 8, 2023

MongoDB has achieved the formal FedRAMP® Moderate Authorized designation for MongoDB Atlas for Government (US), the most secure way for the US Government to deploy, run, and scale MongoDB in the cloud. Additionally, MongoDB has worked with an independent auditor to validate our ability to support customers subject to Criminal Justice Information Services (CJIS) requirements regarding how sensitive data is created, viewed, modified, transmitted, disseminated, stored, and destroyed.

MongoDB Atlas for Government

Atlas for Government is an independent, dedicated environment of MongoDB Atlas for the US public sector, as well as ISVs looking to build US public sector offerings. This developer data platform – an integrated set of data and application services that share a unified developer experience – supports a wide range of use cases including transactional workloads, time series data, search, and petabyte data storage.

Built on AWS and running in US AWS regions, Atlas for Government has been generally available since June 2021 and provides the simplest way to deploy, operate, and scale modern applications, all in a FedRAMP Moderate Authorized environment. Atlas for Government highlights include:

MongoDB clusters deployed in AWS GovCloud or AWS US East/West (US) regions, and leverage the full functionality of MongoDB's document database, Atlas Search, fully automated backup, time series, and more.
Guaranteed high availability with a ~99.995% uptime SLA which auto-scales up or down to accommodate fluctuations in data consumption, affording greater flexibility and cost control.
Unparalleled security, with all security features built-in at no additional cost. Also, Atlas for Government is operated by MongoDB employees who are US persons on US soil.
Support for both AWS GovCloud regions so customers can create multi-GovCloud region clusters and backups that stay within those regions and copy to both.
ISVs can use Atlas for Government to store US government data and rapidly build their own FedRAMP offerings. All encryption within Atlas for Government is FIPS validated.

These features make Atlas for Government uniquely positioned to support mission-critical applications across the US public sector.

How MongoDB powers key use cases across the public sector

MongoDB Atlas is already powering innovative applications in a number of sectors. And now, Atlas for Government is primed to power critical applications across public sector agencies and the ISVs that support them.

Healthcare

MongoDB is built to bring together data from disparate databases, systems, and data formats to create a single view of the patient. And with Atlas for Government’s dynamic schema, government agencies can enrich their view of patients with data from new sources, such as connected health devices. Both MongoDB and FHIR natively support the JSON format, the standard that supports rich data structures and objects prevalent in healthcare such as patient data, claims, policies, and treatment information.

Financial services

Agencies that participate in financial services activities must fully commit to digital transformation – liberating data, empowering developers, and embracing disruption — to keep up with the expectations of instantaneous transactions. Whether it's trading platforms and end-to-end digital loan origination, or AI/ML-driven fraud detection systems and financial 'super apps', Atlas for Government enables innovation and speed for government agencies that conduct payments and core banking applications.

Federal, state, and local government

National, regional, and local governments are facing pressing challenges with rising costs, changing regulations, and complex technological demands. The traditional systems currently in place are expensive and improperly equipped to handle modern needs for scale, cost efficiency, and flexibility. Atlas for Government opens doors for new initiatives like building smart cities, planning for traffic and construction updates, and improving the welfare of citizens.

Education

From groundbreaking data-based research to the administrative management of schools’ complex ecosystems, proper data management can transform how educational institutions operate. A modern data platform helps institutions navigate complex challenges like providing continuous learning, teaching with limited resources, and retaining students and staff. Atlas for Government offers an intuitive, secure, cost-effective solution for institutions dedicated to all stages of education.

How do I get started?

Customers can fill out the form on the MongoDB Atlas for Government page and a MongoDB specialist will get in touch with further details to set up. The specialist will help you set up Atlas for Government clusters (US) and you can either launch a new workload, migrate your existing Atlas workload to Atlas for Government, or re-platform your existing workloads by engaging with our professional services. Please also refer to the technical documentation for Atlas for Government for more details, or learn more on MongoDB University.

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Turning Data Points Into Actionable Insights: Meet May Hoque

>> Announcement: Some features mentioned below will be deprecated on Sep. 30, 2025. Learn more . Imagine the interesting insights you could glean from combining multiple data sources with one tool that helps you easily analyze data over time. May Hoque is a senior software engineer on MongoDB’s Atlas Data Federation team where he helps create a distributed, federated query engine that can query across data stored in multiple sources. Keep reading to find out more about his experience joining MongoDB as an intern and new grad, then continuing to grow his career here over the last four and a half years. Jackie Denner: Thanks for sharing more about your experience today, May! To start, will you give an overview on your software engineering background and how you started working with MongoDB? May Hoque: I began exploring computer science in a high school class. The class was rudimentary but I had fun learning how to build programs. I chose computer science as my university major because it felt like a career I could grow with that both piqued my interest and offered long-term stability. I am currently a senior software engineer on MongoDB’s Atlas Data Federation team. I first joined MongoDB in 2017 as an intern, then returned after graduation to participate in the New Grad Program in 2018 which gave me an opportunity to rotate working between three different teams at MongoDB over our first six months. I originally joined the BI connector team, but then switched to the Atlas Data Federation team. JD: Tell me more about the Atlas Data Federation product. MH: Atlas Data Federation is a distributed, federated query engine at its core. This core enables users to query multiple data sources with a single query, from a single interface. Other MongoDB products, including Atlas Online Archive and Atlas Data Lake , use this core as a building block for their own functionality. The Atlas Data Lake product, for example, orders and organizes data to optimize for super fast queries even as the user's data sources grow in volume. The ability to perform complex queries, even across multiple data sources unlocks valuable benefits for a variety of use cases, for example maintaining the ability to easily query less frequently used data even after archiving it from pre-existing database clusters to less expensive locations. JD: What makes Atlas Data Federation unique? MH: We’re more than just a search function — we can also store your data and organize it in a way that makes it really fast to actually answer those questions. Its integration with Atlas and the larger MongoDB ecosystem widens the scope of the value users can get from their databases. It’s convenient and operationally simple to have all of your solutions to different challenges in the same place. MongoDB Atlas Data Lake allows developers to easily store and analyze large amounts of data in a cost-effective and scalable manner without having to worry about the underlying infrastructure. JD: Talk me through some example use cases your team supports. MH: The real value in large data sets lies in understanding the trends and relationships between the data points. There are endless possibilities of how organizations can use Atlas Data Federation to draw insights to motivate strategic business decisions, from answering questions about specific events, to aggregating insights across a group of data points. Atlas Data Lake stores and organizes your data in a way that makes it really fast to answer questions related to your collection of data. Teams across an organization can benefit from more insight into data learnings. A marketing team may want to know what percentage of their users have spent more than a specific amount on a single item, including supporting data like what the item was and when they purchased it. An investor may want to know how much profit an organization made over a specific time period. A product team may want to look at historical sales data from past product launches. Users can answer all of these questions and more with a query on Atlas Data Federation. JD: What projects are you currently working on? MH: I am contributing to a bigger MongoDB initiative to add more sources of data. Adding this support to Atlas Data Federation and Data Lake will make our service available to new clients who want to use the product, but currently can’t. I’m also working on a high level systems design challenge to rearchitect our systems to scale and improve our service for our customers. JD: Let’s talk about what it’s like to work at MongoDB. What makes the team and product exciting to work on? MH: The Atlas Data Federation team is primarily focused on problems relating to complex distributed systems and database engineering . These challenges aren’t often easy to work on, but the careful and rigorous thinking needed to solve them is exciting and rewarding. Plus, the solution to the data lake problem is in demand, and the projects we work on are relevant to the industry. JD: What is the overall engineering culture like at MongoDB? What opportunities have inspired you to grow here? MH: My experience on the team has contributed to my growth as an engineer. I’ve noticed a strong culture of learning, mentorship and diversity both on the Atlas Data Federation team and the company at large. I appreciate that our team has a wide spectrum of experience levels, from new grads to engineers with decades of experience. The team is collaborative and takes pride in supporting each other. Whether I work on a project independently or with a group of engineers, I’m never working solo. I always have the support of the team and people to bounce ideas off of throughout a project, which creates opportunity for growth. JD: Why should someone join the Atlas Data Federation team? MH: If you're someone who really likes technical challenges or you just want to solve really cool problems, we have no shortage of them to work on. If you’re focused on growth, we have opportunities for all levels of experience. It is possible to grow from an intern to a manager on our team because of the mentorship and breadth of projects available to work on, which I’ve seen happen for some of my colleagues. Our team environment is built on empathy and collaboration. JD: What stands out to you about your overall experience working at MongoDB compared to your past experiences? MH: After a few years on the team, I'm still consistently growing my skill set and working on interesting, fun projects – two primary reasons I continue to work at MongoDB. The problems the Atlas Data Federation team works on provide me useful experience that I can apply to future projects and challenges. If you’re looking to collaborate with forward-thinking teams and interesting use cases, MongoDB is one of the best tech companies to work for. Interested in transforming your career at MongoDB? View open roles on our teams across the globe.

February 7, 2023

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MongoDB Database Observability: Integrating with Monitoring Tools

This post is the final in a three-part series on leveraging database observability. Welcome back to our series on Leveraging Database Observability! Our previous post showcased a real-world use case highlighting how MongoDB Atlas’s observability tools effectively tackle database performance challenges. Whether you’re a developer, DBA, or DevOps engineer, our mission is to empower you to harness the full potential of your data through our observability suite . Integrating Atlas metrics with your central enterprise observability tools can simplify your operations. By seamlessly working with popular observability tools, our approach helps teams streamline workflows and enhance visibility across systems. Integrating MongoDB Atlas with third-party monitoring tools MongoDB’s developer data platform combines all essential data services for building modern applications within a unified experience. Our purpose-built observability tools for Atlas environments offer automatic monitoring and optimization, guiding diagnostics tailored specifically for MongoDB. Additionally, we extend Atlas metrics into your existing enterprise observability stack, enabling seamless integration without replacing your current tools. This creates a consolidated, single-pane view that unifies Atlas telemetry with other tech and application metrics, ensuring comprehensive visibility into both database and full-stack performance. This integration empowers you to monitor, receive alerts, and make data-driven decisions within your existing workflows, driving greater efficiency. Below is a quick guide to modifying integration settings through the Atlas UI and the popular integrations we support: Navigate to the Project Integrations page in Atlas. Choose the organization and project you want to configure from the navigation bar. On the Project Integrations page, select the third-party services you’d like to integrate. Configure the chosen services with the required API keys and regions. Critical integrations for your observability platform With Atlas’s Datadog and Prometheus integrations, you can send critical MongoDB metrics to these platforms, empowering detailed, real-time monitoring. Through Datadog , you can track database operation counts, query efficiency, and resource usage, ideal for pinpointing bottlenecks and managing resources. Similarly, Prometheus enables you to monitor essential metrics like query times, connection rates, and memory usage, supporting flexible tracking of database health and performance. Both integrations facilitate proactive detection of issues, alert configuration for resource thresholds, and a cohesive view of Atlas data when visualized in Grafana. Atlas’s integration with PagerDuty streamlines incident management by sending metrics like performance alerts, billing anomalies, and security events directly to PagerDuty. This integration records incidents automatically, notifies teams upon alerts, and supports two-way syncing, ensuring resolved alerts in Atlas are reflected in PagerDuty. It enables efficient incident response and resource allocation to maintain system stability. With Atlas integrations for Microsoft Teams and Slack, you can route key metrics—such as query latency, disk usage, and throughput—to these channels for timely updates. Teams can use these insights for real-time performance monitoring, incident response, and collaboration. Notifications through these platforms ensure your team stays informed on database performance, storage health, and user activity changes as they occur. Use case: Centralized observability with MongoDB Atlas, Datadog, and Slack Let’s walk through a hypothetical scenario for ShopSmart, an e-commerce company that leverages MongoDB Atlas to manage its product catalog and customer data. As traffic surges, the DevOps team faces challenges in monitoring application performance and database health effectively. To tackle these challenges, the team leverages MongoDB Atlas’ integration with Datadog and Slack, creating a powerful observability ecosystem. Integrating MongoDB Atlas with Datadog: The team pushes key MongoDB Atlas metrics into Datadog, such as query performance, connection counts, and Atlas Vector Search metrics. With Datadog, they can visualize these metrics and correlate overall MongoDB performance with their other applications. Out-of-the-box monitors and dedicated dashboards allow the team to track metrics like throughput, average read/write latency, and current connections. This visibility helps pinpoint bottlenecks in real time, ensuring optimal database performance and improving overall application responsiveness. Setting up alerts in Datadog: The team configures alerts for critical metrics like high query latency and increased error rates. When thresholds are breached, Datadog instantly notifies the team. This proactive approach allows the team to address potential performance issues before they impact customers. Integrating Datadog with Slack: To ensure fast communication, alerts are sent directly to the dedicated Slack channel, “ShopSmart-Alerts.” This integration fosters seamless collaboration, enabling the team to discuss and resolve issues in real-time. With these integrations, ShopSmart’s engineering team can monitor performance quickly and address issues efficiently. The unified observability approach enhances operational efficiency, improves the customer experience, and supports ShopSmart’s competitive edge in the e-commerce industry. By leveraging MongoDB Atlas, Datadog, and Slack, the team ensures scalable performance and drives continuous innovation. Conclusion MongoDB Atlas empowers developers and organizations to achieve unparalleled observability and control over their database environments. By seamlessly integrating with central enterprise observability tools, Atlas enhances your ability to monitor performance metrics and ensures you can do so within your existing workflows. This means you can focus on building modern applications confidently, knowing you have the insights and alerts necessary to maintain optimal performance. Embrace the power of MongoDB Atlas and transform your approach to database management—because your applications can thrive when your data is observable. And that wraps up our Leveraging Database Observability series! We hope you learned something new and found value in these discussions. Sign up for MongoDB Atlas , our cloud database service, to see database observability in action. To dive deeper and expand your knowledge, check out this learning byte for more insights on the MongoDB observability suite and how it can enhance your database performance.

November 14, 2024